Benchmark: math pow (with few extra variants, but without multiplication example and it's pow 8, not pow 2)

Script Preparation code:

function powNaive(x, y) {
	if (!y) return 1;
	let tmp = x;
	for (let i = 1; i < y; i++) {
		tmp *= x;
  	}
	return tmp;
}

// from https://codereview.stackexchange.com/a/217369
function pow2B(x, y) {
    if (y < 2) { return y ? x : 1 }
    if (y & 1) { return x * pow2B(x, y & 0x7FFFFFFE)}
    const p = pow2B(x, y >> 1);
    return p * p;
}

// other two functions from the same stackexchange post
function pow(x, y) {
  if (!y) { return 1 }
  let tmp = res = x;
  for (let i = 1; i < y; i++) {
    for (let j = 1; j < x; j++) { tmp += res }
    res = tmp;
  }
  return res;
}

function pow2(x, y) {
  if (!y) { return 1; }
  if (y % 2) {
    return x * pow2(x, y - 1);
  }
  const p = pow2(x, y/2);
  return p * p;
}

Tests:

Math.pow
var x = Math.pow(54, 8);
pow2 bitwise
var y = pow2B(54, 8)
pow2 summ
var y = pow(54, 8)
pow2 multi
var y = pow2(54, 8)
pow (mult for loop)
var y = powNaive(54, 8)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.pow
pow2 bitwise
pow2 summ
pow2 multi
pow (mult for loop)

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net!

**Benchmark Definition**

The provided JSON represents a benchmark definition for several JavaScript functions that implement exponentiation using different approaches:

1. `powNaive(x, y)`: A naive recursive implementation with a loop to calculate the power.
2. `pow2B(x, y)`: An iterative implementation using bit manipulation ( bitwise operations).
3. `pow2(x, y)`: Another iterative implementation using bit manipulation.
4. `pow(x, y)`: A summation-based implementation that uses nested loops.

Each of these implementations is compared to measure their performance.

**Comparison Options**

The benchmark tests the following options:

*   `powNaive(x, y)` vs. `Math.pow(x, y)`
*   `pow2B(x, y)` vs. `Math.pow(x, y)`
*   `pow2(x, y)` vs. `Math.pow(x, y)`
*   `pow(x, y)` vs. `Math.pow(x, y)`

These comparisons aim to determine which implementation is the most efficient.

**Pros and Cons**

Here's a brief analysis of each approach:

1.  **`powNaive(x, y)`**: This recursive implementation has a time complexity of O(y), making it less efficient than other approaches for large exponents.
2.  **`pow2B(x, y)`**: Bit manipulation is an efficient way to calculate powers, especially when dealing with large numbers and exponents. However, the implementation may be less intuitive for those without prior experience with bitwise operations.
3.  **`pow2(x, y)`**: Similar to `pow2B`, this approach also utilizes bit manipulation but might be slightly more complex due to its use of division instead of AND operation.
4.  **`pow(x, y)`**: This summation-based implementation has a time complexity of O(y \* x), which can become inefficient for large exponents or numbers.

**Other Considerations**

Keep in mind that the choice of implementation depends on specific requirements and constraints:

*   Code readability and maintainability might be more important than absolute performance.
*   Development speed and ease of testing might outweigh raw performance gains.
*   The target platform (e.g., mobile, web) can influence the best approach due to differences in computational resources.

**Library Usage**

None of the implementations provided use external libraries. However, `Math.pow` relies on a built-in JavaScript function for exponentiation, which may involve additional overhead not accounted for in this benchmark.

**Special JS Features/Syntax**

The implementations mentioned earlier do not employ any special JavaScript features or syntax beyond what's standard in modern JavaScript. If these benchmarks were to be modified to utilize features like async/await or modern iteration protocols (e.g., `for...of`, `for...in`), it could impact performance.

Now that we've explored the details of this benchmark, feel free to ask any follow-up questions!

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Math.pow	15784721.0 Ops/sec
pow2 bitwise	7454481.5 Ops/sec
pow2 summ	43277.2 Ops/sec
pow2 multi	5733162.5 Ops/sec
pow (mult for loop)	30622784.0 Ops/sec

Related benchmarks:

math pow (with few extra variants, but without multiplication example and it's pow 8, not pow 2) (version: 0)

Comparing performance of: Math.pow vs pow2 bitwise vs pow2 summ vs pow2 multi vs pow (mult for loop)

Created: one year ago by: Guest

Jump to the latest result

Math.pow

pow2 bitwise

pow2 summ

pow2 multi

pow (mult for loop)

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):